... for estimating and correcting water velocity changes on 4D seismic datasets. Each sail line is migrated independently and Common Depth Point (CDP) gathers are output for the overburden along a subsurface strip for both vintages. The 4D approach consists of performing cross-correlations using collocated CDPs...

... We present an automatic workflow to estimate anisotropic parameters in vertical transverse isotropic (VTI) media. A cascaded approach is adopted to scan for the stacking velocity and the anisotropic parameters sequentially. The dynamic programming algorithm is applied to automatically pick...

... We developed a system (D-Sharp) for seismic depth uncertainty estimation. D-Sharp uses 3D physics with waveforms to make robust depth uncertainty assessments of models from pre-stack seismic data. It consists of three major components: 1) generating a set of trial models, 2) generating seismic...

... Understanding the anisotropy parameters of organic-rich shale formations is important to interpret seismic amplitude variation with offset (AVO) data and estimate shale-specific reservoir properties more accurately. In general, we can quantify the elastic stiffness coefficients and Thomsen...

... We present a novel workflow for the accelerated signal enhancement of massive 3D prestack seismic data utilizing a Local Wavefront Attributes Deep Neural Network. It is based on automatic local wavefront attributes estimation using a specially trained convolutional deep neural network...

... As field data applications of FWI increase, dealing with both random and coherent noise in seismic data, and the artifacts they create in FWI models, becomes increasingly important; noise suppression or estimation is also increasingly important when we transition to elastic multiparameter...

... inversion american association inversion fwi subsurface storage reservoir characterization applied geoscience energy 10 workflow saline aquifer monitoring estimation Synthetic time-lapse FWI analysis for designing cross well seismic survey during CO2 injection in a depleted oil field Toru...

... This paper will focus on a data driven approach for reservoir properties estimation of a recently acquired and processed multi-azimuth multisensor survey in the prolific South Viking Graben, Norway. This case study will review the main benefits over various stratigraphic interval...

... Accurate estimation of water content in the soil is a major goal in a variety of agricultural or engineering projects. As soils can have different physical behaviors depending on their water content, it is important to know soil water content at any time during imbibition or drainage. In 1942 G...

... Determination of seismic lithology, porosity, and pore fluid requires detailed modeling of petrophysical logs to improve the correlation with a seismic AVO response. Unfortunately, acquiring a full set of logs for all wells in a seismic survey is unpractical, and estimating sonic, shear...

... We often apply a number of processing modules to a field dataset to perform various tasks, like denoising, first arrival picking, velocity estimation, and so on. Selecting the architecture, collecting labels, and tuning a deep-learning network for a specific seismic processing task have been...

... Full waveform inversion (FWI), as an optimization-based approach in estimating subsurface models, is limited by incomplete acquisition and illumination of the subsurface. Adding data corresponding to new and independent ray paths as input could lead to significant increases in the reliability...

... the pressure changes from the reservoir simulation to the estimated pressure changes from observations of 4D time-strains and measurements of elastic properties within the reservoir. We apply this method to analyze the Fulmar Formation for the Shearwater Field case study. By generating multiple scenarios...

... gas field in the Netherlands by integrating a suite of DL models, which enable robust well log QC, accurate relative geologic time reconstruction, automated seismic structure interpretation, and integrated property estimation, respectively. The estimated density, velocity and porosity models...

... and time-lapse seismic, assembled through fluid flow modeling. artificial intelligence exploration geophysicist international porosity american association formulation reservoir simulation estimation node upstream oil & gas reservoir characterization applied geoscience graph society...

... angle may be different than the nominal pitch angle, we propose a method to estimate pitch angle and helical trace spacing by cross-correlation with co-located datasets. For a cable with a nominal pitch angle of 30.0 degrees (520 traces per 300 m), cross-correlation with straight fiber data gives...

... classical regularization theory with a learned deep decomposition framework. The method extends the popular learned post-processing approach by learning how to improve an initial reconstruction with estimated missing components from the null space of the forward operator, which in our case, are the missing...

... Full waveform inversion (FWI) is a standard and automated approach that allows to estimate subsurface properties such as acoustic/elastic velocity model. Nevertheless the methodology is known for complicated convergence properties and non-uniqueness of the obtained solution. A common practice...

... Generating plausible 3D velocity and anisotropy parameters plays an important role in various seismic analyses such as depth uncertainty estimation. In this paper, we present a 3D stochastic method for generating velocity and anisotropy parameters models in vertical transverse isotropy (VTI...

... In seismic interpretation, deep learning models frequently overfit to limited amount of annotated data. For this reason, well calibrated models and reliable uncertainty estimation are essential for the adoption of deep learning in modern interpretation workflows. However, existing approaches...